Methods for Advanced Wind Turbine Condition Monitoring and Early Diagnosis: A Literature Review

Md Liton Hossain, Ahmed Abu-Siada and S. M. Muyeen
Additional contact information
Md Liton Hossain: Department of Electrical and Computer Engineering, Curtin University, Kent Street, Bentley, Perth, WA 6102, Australia
Ahmed Abu-Siada: Department of Electrical and Computer Engineering, Curtin University, Kent Street, Bentley, Perth, WA 6102, Australia
S. M. Muyeen: Department of Electrical and Computer Engineering, Curtin University, Kent Street, Bentley, Perth, WA 6102, Australia

Energies, 2018, vol. 11, issue 5, 1-14

Abstract: Condition monitoring and early fault diagnosis for wind turbines have become essential industry practice as they help improve wind farm reliability, overall performance and productivity. If not detected and rectified at early stages, some faults can be catastrophic with significant loss or revenue along with interruption to the business relying mainly on wind energy. The failure of Wind turbine results in system downtime and repairing or replacement expenses that significantly reduce the annual income. Such failures call for more systematized operation and maintenance schemes to ensure the reliability of wind energy conversion systems. Condition monitoring and fault diagnosis systems of wind turbine play an important role in reducing maintenance and operational costs and increase system reliability. This paper is aimed at providing the reader with the overall feature for wind turbine condition monitoring and fault diagnosis which includes various potential fault types and locations along with the signals to be analyzed with different signal processing methods.

Keywords: wind turbine; condition monitoring; fault diagnosis; signals; signal processing methods (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/5/1309/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/5/1309/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:5:p:1309-:d:148122

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().